A way forward to increase the success of policies which is increasingly discussed is the formulation of a policy package, rather than a combination of measures considered and deployed in isolation. Policy measures are the building blocks of policy packages and primary measures ‐ those policy measures that can directly affect the policy objectives – are the foundations of every package. In the process of formulating a policy package to address a certain policy problem, which is briefly discussed in this paper, an important step is deciding ‘what to start with’ given the range of primary measures available. This essentially involves a process of ranking the alternatives, commonly done using multi‐criteria decision making (MCDM) techniques. In this paper a new methodology for analysis and ranking of policy measures is introduced which combines network analysis and MCDM tools. This methodology not only considers the internal properties of the measures but also their interactions with other potential measures. Consideration of such interactions provides additional insights into the process of policy formulation and can help the domain experts and policymakers to better assess the policy measures and to understand the complexities involved. This new methodology is applied in this paper to the formulation of a policy to increase Walking and Cycling. The results demonstrate the advantages of such a method over the traditional MCDM ranking and the usefulness of the information provided by the policy measure network in the visualisation and analysis of the network structures. Such visualisation can clearly identify for policy makers the effects of the interaction between the measures and of their centrality on their likely effectiveness in influencing the policy targets or their (in)efficiency with respect to implementation and their dependence on other measures
